339 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" PhD scholarships in United Kingdom
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not essential How to apply: Interested candidates should submit an expression of interest by sending a CV and supporting statement outlining their skills and interests in this research area to https
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. During the PhD programme, a student would be expected to explore the design of advanced computer networks, both through simulation and the direct execution of workloads on real-world implementations. As
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Application deadline: 30/05/2026 How to apply: https://uom.link/pgr-apply-2425 This 4-year PhD studentship is open to Home (UK) applicants. The successful candidate will receive an annual tax-free
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We are recruiting a new fully-funded PhD student to join Dr Daniel Yon’s Uncertainty Lab at the School of Psychological Sciences at Birkbeck, University of London. This post is attached to a recent grant awarded to Dr Yon from the Leverhulme Trust entitled Public Communication and Private...
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tailored trajectory guidance. Enhancing Robot Autonomy: Enabling robots to improve their own performance by learning from operator data, ultimately enhancing their ability to assist in complex tasks. Key
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, or even months to derive a suitable hardware model. This limitation is only exaggerated when considering the digital representation of multicore computer systems, requiring the modelling of a broad range of
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of Chemistry is a leading international centre for chemical kinetics and its applications. (https://eps.leeds.ac.uk/chemistry ) Task description for your Individual Research Project (IRP) Problem Definition
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to the delivery of the Chair’s programme. More information on the UNESCO Chair in Storytelling Education for Sustainability can be found here: https://www.lboro.ac.uk/schools/design-creative-arts/unesco-chair
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in Experimental Particle Physics (https://www.hep.manchester.ac.uk/study/ ). Our group (https://www.hep.manchester.ac.uk/ ) is one of the largest research groups in the UK with over 100 members
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regions. Machine learning provides a promising route to capture these relationships more systematically by identifying how local geometric features determine the resolution required for reliable prediction